Abstract: In this study, a new bottom-up approach is proposed to predict the crystal structure of the substrate-induced polymorph (SIP) of an archetypal molecular semiconductor. In spite of intense efforts, the formation mechanism of SIPs is still not fully understood, and predicting their crystal structure is a very delicate task. Here, we selected lead phthalocyanine (PbPc) as a prototypical molecular material because it is a highly symmetrical yet nonplanar molecule and we demonstrate that the growth and crystal structure of the PbPc SIPs can be templated by the corresponding physisorbed self-assembled molecular networks (SAMNs). Starting from SAMNs of PbPc formed at the solution/graphite interface, the structural and energetic aspects of the assembly were studied by a combination of in situ scanning tunneling microscopy and multiscale computational chemistry approach. Then, the growth of a PbPc SIP on top of the physisorbed monolayer was modeled without prior experimental knowledge, from which the crystal structure of the SIP was predicted. The theoretical prediction of the SIP was verified by determining the crystal structure of PbPc thin films using X-ray diffraction techniques, revealing the formation of a new polymorph of PbPc on the graphite substrate. This study clearly illustrates the correlation between the SAMNs and SIPs, which are traditionally considered as two separate but conceptually connected research areas. This approach is applicable to molecular materials in general to predict the crystal structure of their SIPs.

Abstract: Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1].   The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions.   We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration.   Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3]   Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference.   Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script.  Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.

Abstract: Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic‐resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state‐of‐the‐art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark‐field scanning transmission electron microscopy enables the acquisition of ten high‐resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allows resolving the real‐time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.

Abstract: Atomically resolved electron energy-loss spectroscopy experiments are commonplace in modern aberration-corrected transmission electron microscopes. Energy resolution has also been increasing steadily with the continuous improvement of electron monochromators. Electronic excitations however are known to be delocalized due to the long range interaction of the charged accelerated electrons with the electrons in a sample. This has made several scientists question the value of combined high spatial and energy resolution for mapping interband transitions and possibly phonon excitation in crystals. In this paper we demonstrate experimentally that atomic resolution information is indeed available at very low energy losses around 100 meV expressed as a modulation of the broadening of the zero loss peak. Careful data analysis allows us to get a glimpse of what are likely phonon excitations with both an energy loss and gain part. These experiments confirm recent theoretical predictions on the strong localization of phonon excitations as opposed to electronic excitations and show that a combination of atomic resolution and recent developments in increased energy resolution will offer great benefit for mapping phonon modes in real space.

Abstract: Quantitative annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique to characterise nano-particles on an atomic scale. Because of their limited size and beam sensitivity, the atomic structure of such particles may become extremely challenging to determine. Therefore keeping the incoming electron dose to a minimum is important. However, this may reduce the reliability of quantitative ADF STEM which will here be demonstrated for nano-particle atom-counting. Based on experimental ADF STEM images of a real industrial catalyst, we discuss the limits for counting the number of atoms in a projected atomic column with single atom sensitivity. We diagnose these limits by combining a thorough statistical method and detailed image simulations.

Abstract: In the present paper, the principles of detection theory are used to quantify the probability of error for atom-counting from high resolution scanning transmission electron microscopy (HR STEM) images. Binary and multiple hypothesis testing have been investigated in order to determine the limits to the precision with which the number of atoms in a projected atomic column can be estimated. The probability of error has been calculated when using STEM images, scattering cross-sections or peak intensities as a criterion to count atoms. Based on this analysis, we conclude that scattering cross-sections perform almost equally well as images and perform better than peak intensities. Furthermore, the optimal STEM detector design can be derived for atom-counting using the expression for the probability of error. We show that for very thin objects LAADF is optimal and that for thicker objects the optimal inner detector angle increases.

Abstract: <script type='text/javascript'>document.write(unpmarked('In this paper, both the frozen lattice (FL) and the absorptive potential (AP) approximation models are compared in terms of the integrated intensity and the precision with which atomic columns can be located from an image acquired using high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM). The comparison is made for atoms of Cu, Ag, and Au. The integrated intensity is computed for both an isolated atomic column and an atomic column inside an FCC structure. The precision has been computed using the so-called Cramer-Rao Lower Bound (CRLB), which provides a theoretical lower bound on the variance with which parameters can be estimated. It is shown that the AP model results into accurate measurements for the integrated intensity only for small detector ranges under relatively low angles and for small thicknesses. In terms of the attainable precision, both methods show similar results indicating picometer range precision under realistic experimental conditions. (C) 2017 Elsevier B.V. All rights reserved.'));

Abstract: This study addresses the comparison of scanning transmission electron microscopy (STEM) measurements of momentum transfers using the first moment approach and the established method that uses segmented annular detectors. Using an ultrafast pixelated detector to acquire four-dimensional, momentum-resolved STEM signals, both the first moment calculation and the calculation of the differential phase contrast (DPC) signals are done for the same experimental data. In particular, we investigate the ability to correct the segment-based signal to yield a suitable approximation of the first moment for cases beyond the weak phase object approximation. It is found that the measurement of momentum transfers using segmented detectors can approach the first moment measurement as close as 0.13 h/nm in terms of a root mean square (rms) difference in 10 nm thick SrTiO3 for a detector with 16 segments. This amounts to 35% of the rms of the momentum transfers. In addition, we present a statistical analysis of the precision of first moment STEM as a function of dose. For typical experimental settings with recent hardware such as a Medipix3 Merlin camera attached to a probe-corrected STEM, we find that the precision of the measurement of momentum transfers stagnates above certain doses. This means that other instabilities such as specimen drift or scan noise have to be taken into account seriously for measurements that target, e.g., the detection of bonding effects in the charge density.

Abstract: A real-time image reconstruction method for scanning transmission electron microscopy (STEM) is proposed. With an algorithm requiring only the center of mass of the diffraction pattern at one probe position at a time, it is able to update the resulting image each time a new probe position is visited without storing any intermediate diffraction patterns. The results show clear features at high spatial frequency, such as atomic column positions. It is also demonstrated that some common post-processing methods, such as band-pass filtering, can be directly integrated in the real-time processing flow. Compared with other reconstruction methods, the proposed method produces high-quality reconstructions with good noise robustness at extremely low memory and computational requirements. An efficient, interactive open source implementation of the concept is further presented, which is compatible with frame-based, as well as event-based camera/file types. This method provides the attractive feature of immediate feedback that microscope operators have become used to, for example, conventional high-angle annular dark field STEM imaging, allowing for rapid decision-making and fine-tuning to obtain the best possible images for beam-sensitive samples at the lowest possible dose.

Abstract: Short-wave infrared (SWIR) fluorescence could become the new gold standard in optical imaging for biomedical applications due to important advantages such as lack of autofluorescence, weak photon absorption by blood and tissues, and reduced photon scattering coefficient. Therefore, contrary to the visible and NIR regions, tissues become translucent in the SWIR region. Nevertheless, the lack of bright and biocompatible probes is a key challenge that must be overcome to unlock the full potential of SWIR fluorescence. Although rare-earth-based core-shell nanocrystals appeared as promising SWIR probes, they suffer from limited photoluminescence quantum yield (PLQY). The lack of control over the atomic scale organization of such complex materials is one of the main barriers limiting their optical performance. Here, the growth of either homogeneous (α-NaYF₄) or heterogeneous (CaF₂) shell domains on optically-active α-NaYF₄:Yb:Er (with and without Ce³⁺co-doping) core nanocrystals is reported. The atomic scale organization can be controlled by preventing cation intermixing only in heterogeneous core-shell nanocrystals with a dramatic impact on the PLQY. The latter reached 50% at 60 mW/cm²; one of the highest reported PLQY values for sub-15 nm nanocrystals. The most efficient nanocrystals were utilized for in vivo imaging above 1450 nm.